import numpy as np

# def conv2D(input_2Ddata, kern, in_size, out_size, kern_size=3, stride=1):
#     # size of input
#     (h1, w1) = in_size
#     # size of output
#     (h2, w2) = out_size
#     # initialize output
#     output_2Ddata = np.zeros(shape=out_size)
#     for i1, i2 in zip(range(0, h1, stride), range(h2)):
#         for j1, j2 in zip(range(0, w2, stride), range(w1)):


if __name__ == "__main__":
    a = np.random.randint(9, size=(3, 3))
    b = np.random.randint(9, size=(3, 3))
    print(a)
    print(b)
    print(a * b)
